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kadam-official

@kadam-net/mcp-server

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kadam_adv_create_bulk_creatives

Queue bulk creative creation from staged images across multiple campaigns. Returns a job for asynchronous processing; check results with kadam_adv_get_bulk_job.

Instructions

Second step of a bulk creative batch: turn staged images into creatives. Every item is created in every listed campaign, so the batch size is items × campaigns. Each item needs a stagedId from kadam_adv_upload_bulk_images. Creation is asynchronous — this call queues the work and returns a job; read the per-row result from kadam_adv_get_bulk_job. Sending the same payload again returns the same job instead of creating the creatives twice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesRows of the batch, one creative per campaign each
campaignIdsYesCampaigns to create the creatives in
pauseAfterModerationNoKeep the creatives paused after they pass moderation

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.1

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=false, so the description carries the real behavioral burden and does it well: asynchronous queueing, a job handle rather than immediate creatives, and idempotency on identical payloads. It also discloses the multiplicative batch semantics (items × campaigns), which materially affects how the agent sizes requests.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five sentences, each carrying distinct information (pipeline position, cross-product sizing, prerequisite, async/job model, idempotency), with the most important framing front-loaded. No filler or restatement of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description still explains what the call returns (a job) and where per-row results are read, plus the async and replay semantics. Combined with 100% schema parameter coverage, an agent has everything needed to invoke and follow up correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning the schema cannot express: every item is fanned out across every listed campaign, and each item requires a stagedId sourced from a specific sibling tool. The remaining params (name, path, text, title, pauseAfterModeration) are left to the schema, which is acceptable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('turn staged images into creatives') and positions itself as 'second step of a bulk creative batch', which separates it from the single-creative sibling kadam_adv_create_creative. An agent can identify the operation without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names the prerequisite step (stagedId from kadam_adv_upload_bulk_images) and the follow-up path for results (kadam_adv_get_bulk_job), giving a full pipeline context rather than isolated usage. The same-payload-replay behavior further tells the agent when re-calling is safe.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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